GPU Cluster Resource Scheduling and Optimization Engineer

About the Role

Together.ai is driving innovation in AI infrastructure by creating cutting-edge systems that enable scalable and efficient machine learning workloads. Our team tackles the unique challenges of resource scheduling, optimization, and orchestration for large-scale AI training and inference systems.

We are looking for a talented AI Workload Resource Scheduling and Optimization Engineer to join our team. This role focuses on designing and implementing advanced scheduling algorithms, resource management strategies, and optimization techniques to maximize performance and minimize costs for large-scale distributed AI workloads.

Responsibilities

• Resource Scheduling and Allocation:
  • Develop and implement intelligent scheduling algorithms tailored for distributed AI workloads on multi-cluster and multi-tenant environments.
  • Ensure efficient allocation of GPUs, TPUs, and CPUs across diverse workloads, balancing resource utilization and job performance.
• Performance Optimization:
  • Design optimization techniques for dynamic resource allocation, addressing real-time variations in workload demand.
  • Implement load balancing, job preemption, and task placement strategies to maximize throughput and minimize latency.
• Scalability and Efficiency:
  • Build systems that efficiently scale to thousands of nodes and petabytes of data.
  • Optimize training and inference pipelines to reduce runtime and cost while maintaining accuracy and reliability.
• Monitoring and Analytics:
  • Build tools for real-time monitoring and diagnostics of resource utilization, job scheduling efficiency, and bottlenecks.
  • Leverage telemetry data and machine learning models for predictive analytics and proactive optimization.
• Collaboration and Innovation:
  • Collaborate with researchers, data scientists, and platform engineers to understand workload requirements and align resource management solutions.
  • Stay updated with the latest trends in distributed systems, AI model training, and cloud-native technologies.

Requirements

Must-Have:

• Experience:
  • 5 years of experience in resource scheduling, distributed systems, or large-scale machine learning infrastructure.
• Technical Skills:
  • Proficiency in distributed computing frameworks (e.g., Kubernetes, Slurm, Ray).
  • Expertise in designing and implementing resource allocation algorithms and scheduling frameworks.
  • Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and GPU orchestration.
• Programming:
  • Proficient in Python, C , or Go for building high-performance systems.
• Optimization Skills:
  • Strong understanding of operational research techniques, such as linear programming, graph algorithms, or evolutionary strategies.
• Soft Skills:
  • Analytical mindset with a focus on problem-solving and performance tuning.
  • Excellent collaboration and communication skills across teams.

Nice-to-Have:

• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX).
• Familiarity with AI-specific workloads like DDP, sharded training, or reinforcement learning.
• Knowledge of auto-scaling and cost-optimization strategies in cloud environments.
• Contributions to open-source scheduling or orchestration projects.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 equity benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy